A commonly used practice to reach spectral efficiency in radio communication systems of today is the use of adaptive modulation and coding (AMC). When applying AMC in a radio communication system, the modulation and coding of data to be transmitted are selected to match the current channel quality, in order to achieve high system throughput and low delay. For example, AMC is used in LTE both in the uplink (UL) and the downlink (DL).
In LTE, an instantaneous downlink channel quality is estimated by a mobile terminal, based on measurements performed on reference signals transmitted from a base station. From the measurements, a channel quality report, e.g. a Channel Quality Indicator (CQI), is derived and transmitted in the uplink to the base station. Then, a modulation order and a code rate to be used when addressing said mobile terminal, can be selected in the base station, at least partially based on the reported quality.
A typical scenario comprising a network node 102 and a mobile terminal 104 is illustrated in FIG. 1. The network node 102 transmits signals 108 to the mobile terminal 104 in the downlink, and the mobile terminal 104 transmits signals 106 to the network node 102 in the uplink. Unwanted signal energy and/or thermal noise, i.e. interference, is illustrated as dashed arrows 110. In the uplink, a channel quality estimate can be obtained from measurements on received mobile terminal transmissions 106. The mobile terminal transmissions 106 may comprise regular data or so called sounding reference symbols. A sounding symbol is a special reference symbol, which is known to the receiver, and is used for channel estimation. The interference 110 experienced in a network node 102, e.g. a base station, can be estimated by measuring, in the network node 102, the total received power, and then subtracting the power of the desired signal 106. The thus obtained interference estimate applies to all mobile terminals in the cell, even mobile terminals which are not currently transmitting. The modulation and coding scheme (MCS) to be used in the uplink is then indicated to the respective mobile terminals in a “grant” message. The grant is transmitted from the base station 102 to the mobile terminal 104 and indicates assigned resources and selected MCS.
Since the MCS must be selected prior to the transmission, it is always based on an estimate or prediction of the actual channel quality during the transmission. More or less advanced schemes can be used in the process of channel quality estimation, but a common strategy is to filter historic channel quality values, and subtract a safety margin, or “back-off”, to compensate for the inherent uncertainty of the estimate.
The MCS should generally be selected to give high spectral efficiency and low packet delay. Often, a block error rate (BLER) target is given as a guideline of a good trade-off between throughput and delay. Different algorithms based on BLER targets are commonly used in communication systems such as High Speed Packet Access (HSPA), where the back-off is typically based on the experienced block error performance. Algorithms based on BLER are typically applied as an outer-loop, adjusting a back-off margin, set by a relatively fast inner-loop, based on e.g. CQI. An example of such an outer-loop algorithm, which is commonly used, is the so called “jump algorithm”, which is further described e.g. in the patent document U.S. Pat. No. 7,310,499.
One of the major drawbacks of previously used outer-loop solutions is that they converge slowly and require a large number of transmissions in order to obtain sufficiently good statistics. This is especially true for low BLER targets. In OFDM-like systems, where mobile terminals can be assigned parts of different size of the frequency-band, the channel quality prediction can be very poor for small parts or allocations comprising few e.g. resource blocks, but quite good for large parts or allocations comprising a comparatively large number of resource blocks. To handle this difference with one of said previously known outer-loop algorithms would slow it down even further.
Consequently, it is a problem that the above described estimation and adjustment of a link adaptation (LA) margin is slow, which has a negative effect on the efficiency in radio link resource utilization, especially at low to medium traffic loads.